}
    }

    private fun isDot(input: String): Boolean {
      return input == "." || input.equals("%2e", ignoreCase = true)
    }

    private fun isDotDot(input: String): Boolean {
      return input == ".." ||
        input.equals("%2e.", ignoreCase = true) ||
        input.equals(".%2e", ignoreCase = true) ||
        input.equals("%2e%2e", ignoreCase = true)
    }

    /**

  }

  /**
   * Returns a {@code Future} whose result is taken from the given primary {@code input} or, if the
   * primary input fails with the given {@code exceptionType}, from the result provided by the
   * {@code fallback}. {@link AsyncFunction#apply} is not invoked until the primary input has
   * failed, so if the primary input succeeds, it is never invoked. If, during the invocation of

  }

  /**
   * Returns a {@code Future} whose result is taken from the given primary {@code input} or, if the
   * primary input fails with the given {@code exceptionType}, from the result provided by the
   * {@code fallback}. {@link AsyncFunction#apply} is not invoked until the primary input has
   * failed, so if the primary input succeeds, it is never invoked. If, during the invocation of

//          automatic skipping of dummy input operations is performed.
//  ninputs - number of elements in `inputs` array
//  inputs - array of TF_Outputs that specify the inputs to the function.
//           If `ninputs` is zero (the function takes no inputs), `inputs`
//           can be null. The names used for function inputs are normalized

			input:      testInput,
			query:      `select id from S3Object s WHERE s.id in [4,3]`,
			wantResult: ``,
		},
		{
			name:       "select-float-by-val",
			input:      testInput,
			query:      `SELECT num2 from s3object s WHERE num2 = 0.765111`,
			wantResult: `{"num2":" 0.765111"}`,
		},
		{
			name:       "select-non_exiting_values",
			input:      testInput,

  TFE_DeleteContextOptions(opts);

  TFE_TensorHandle* input1 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* input2 = TestMatrixTensorHandle(ctx);
  TFE_Op* identityOp = TFE_NewOp(ctx, "IdentityN", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_TensorHandle* inputs[] = {input1, input2};
  TFE_OpAddInputList(identityOp, inputs, 2, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

                }
              ],
              "traffic_direction": "INBOUND",
              "internal_listener": {},
              "filter_chain_matcher": {
                "matcher_tree": {
                  "input": {
                    "name": "ip",
                    "typed_config": {
                      "@type": "type.googleapis.com/envoy.extensions.matching.common_inputs.network.v3.DestinationIPInput"
                    }

                }
              ],
              "traffic_direction": "INBOUND",
              "internal_listener": {},
              "filter_chain_matcher": {
                "matcher_tree": {
                  "input": {
                    "name": "ip",
                    "typed_config": {
                      "@type": "type.googleapis.com/envoy.extensions.matching.common_inputs.network.v3.DestinationIPInput"
                    }

  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};
    std::unique_ptr<TF_WhileParams> params(new TF_WhileParams(
        TF_NewWhile(func_graph_, &inputs[0], inputs.size(), s_)));

		input[i] = byte(i % 251)
		if i%101 == 0 {
			input[i] ^= byte(i / 101)
		}
	}
	return input
}

func TestReaderWriteTo(t *testing.T) {
	input := createTestInput(8192)
	r := NewReader(onlyReader{bytes.NewReader(input)})
	w := new(bytes.Buffer)
	if n, err := r.WriteTo(w); err != nil || n != int64(len(input)) {
		t.Fatalf("r.WriteTo(w) = %d, %v, want %d, nil", n, err, len(input))
	}